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Liou, Gloria; Bonner, Cavan V.; Tay, Louis – International Journal of Testing, 2022
With the advent of big data and advances in technology, psychological assessments have become increasingly sophisticated and complex. Nevertheless, traditional psychometric issues concerning the validity, reliability, and measurement bias of such assessments remain fundamental in determining whether score inferences of human attributes are…
Descriptors: Psychometrics, Computer Assisted Testing, Adaptive Testing, Data
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Morris, Scott B.; Bass, Michael; Howard, Elizabeth; Neapolitan, Richard E. – International Journal of Testing, 2020
The standard error (SE) stopping rule, which terminates a computer adaptive test (CAT) when the "SE" is less than a threshold, is effective when there are informative questions for all trait levels. However, in domains such as patient-reported outcomes, the items in a bank might all target one end of the trait continuum (e.g., negative…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Banks, Item Response Theory
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Luo, Xiao; Wang, Xinrui – International Journal of Testing, 2019
This study introduced dynamic multistage testing (dy-MST) as an improvement to existing adaptive testing methods. dy-MST combines the advantages of computerized adaptive testing (CAT) and computerized adaptive multistage testing (ca-MST) to create a highly efficient and regulated adaptive testing method. In the test construction phase, multistage…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Construction, Psychometrics